A variety of spontaneous gestures, like fingers, hands, head or body movements are used to communicate to a large number of people. Gestures are also considered to be a natural communication channel for human computer interaction. Most of our interactions with computers are performed with traditional keyboards, mouse, and remote controls. Various gesture-based interfaces can serve as an alternate for controlling computers, e.g. to navigate in office applications or to play some console games like the Nintendo Wii.

Gesture recognition is the process of recognizing and interpreting various movements of the hands, arms, face, or sometimes head.

Gesture recognition has already made its place in media and gaming markets and is now expanding its wings across various other fields. It allows humans and machines to interface more easily. With the technological advancement, various low-cost MEMS (Micro-Electro-Mechanical Systems) are inserted in mobile devices, such as mobile phones, and other portable personal electronic devices. It provides new possibilities for interacting with various applications.

Gesture recognition enables natural interactions with the various devices that surround us, like a person controlling the TV with simple hand movements.

Existing Off-the-shelf solutions

A Glove-Based Gesture Recognition system consists of a glove or sensors for data processing and power supply. The glove worn by the user extracts features concerning the configuration of his/her hand together with its movement. By analyzing and interpreting these features, one can extract information about the ongoing gesture. The users are made to wear the additional equipment which may burden the actual interaction.

Vision-based techniques use visual inputs in order to extract the features to be used in the gesture recognition. It provides the comfortable feeling of natural interaction to the user. Vision-based techniques have overcome the problem of Glove-Based techniques, but are occupied with other problems. Portability is an issue for most vision systems that require still placements of the video cameras. Processing video information has several problems as they are highly dependent on the environment, light conditions, video camera settings.

Limitations of existing solutions

Solutions available today caters the business need of gesture recognition but are accompanied with many shortcomings. The solutions available are tightly coupled with the hardware and offers very less or no flexibility. This makes it impossible to port gesture recognition application on another hardware platform.

Most of the solutions come up with pre-defined cameras. The camera interface is either integrated in the solution or is the one supported by the solution. This makes the solution highly dependent on the camera and does not allow the flexibility to use any other camera.

Gesture recognition is entering into many facets like automobile, healthcare etc. Most of the solutions cater to the need of specific OEM. If the solution is designed for automobile, it will have the SDK designed specifically for automobile gesture recognition applications.

Proposed solution for ALL

Devise a solution that revolutionizes the way one interacts with the digital device. The solution should aim at overcoming the limitations of the existing solutions available in the market. Unlike the solutions available today, the proposed solution should support multiple hardware platforms. It should act as glue between the underlying hardware and the gesture recognition application. If any application is developed on a platform using the proposed solution it can be easily run on another platform.

The solution should be flexible enough to operate on input acquired by widely used and supported cameras.

The solution should be used in developing video-based gesture recognition applications. It therefore will not require any markers or special gloves to obtain the input from the user.

Reduce the development time for gesture recognition applications.

Easily scalable to add more gestures.

Target multiple areas like automobile, medical, education. The interfaces of the solution will designed in a way that facilitates its usage across many market areas.

Solution allows developers to create the application quickly and easily. Thereby, saving the development time and effort and speeding the application availability in market.

Solution usage in Gesture Recognition

Various vision based gesture applications for markets such as TV and gaming, automobile, healthcare, interactive displays and many others can be built on top of the proposed solution.

Automobile
Gesture recognition allows automobile manufacturers to add more value to their offerings. Intuitive car infotainment solutions enable the user to explore maps; toggle menus and radio stations using simple hand gestures. The solution will serve as a wrapper for developing car infotainment applications that uses finger-tracking based gestures.

Video security and analytics
Most surveillance facial recognition systems only automatically check every person against a database of known suspects. It makes difficult for securities catch someone who has the intentions of doing any forbidden act. Gesture recognition facilitates reading human facial expressions of people in that area. The application helps in understanding what their expressions show or they are about to commit a prohibited piece of work. Gesture recognition application that facilitates people counting can be developed. Such applications can be very useful to track the number of people in a gathering, or in case of law situations where gathering is prohibited, to check the number of persons standing at one place.
The solution allows developing various gesture recognition applications in the field of video security. It allows widely used camera to be used for the application. Using the solution also facilitates running application on multiple platforms.

Healthcare Aids
The motive is to develop a video-based hand gesture recognition system to be used as a sign language interpreter. A sign language is a language commonly used by physically impaired people who cannot speak and hear.
The proposed solution helps in developing an application that translates sign language to meaning commands. The gesture recognition application is used as an interface for deaf/dumb people.
The proposed solution allows this application to be hardware independent making it possible to run on different hardware platforms.

Conclusion

The end user is now moving towards a whole new path of human machine interaction. This is creating a demand for enabling gesture recognition in every facet of the market.

One can think across the boundary to use the solution in video-based gesture recognition application.